Dietary fat: assessing the evidence in support of a moderate-fat diet; the benchmark based on lipoprotein metabolism
Bibliographic record
Abstract
There is a growing database that has evaluated the effects of varying amounts of total fat on risk factors for cardiovascular disease, diabetes and overweight and obesity. The evidence clearly suggests that extremes in dietary fat should be avoided, and instead a diet moderate in total fat (25-35 % energy) is preferable for the majority of individuals. Moreover, we now appreciate the importance of individualizing dietary fat recommendations within this range of total fat. With respect to cardiovascular disease, a diet higher in total fat (30-35 % energy) affects the lipid and lipoprotein risk profile more favourably than a lower-fat diet; this is also the case for individuals with diabetes, with the added benefit of better glycaemic control. Dietary fibre (> or = 25 g/d) attenuates and even prevents the potentially adverse lipid and lipoprotein effects of a lower-fat diet. With respect to weight control, a moderate-fat diet can be as, or even more, effective than a lower-fat diet, because of advantages with long-term adherence and potentially favourable effects on lipids and lipoproteins. Thus, there is now a convincing scientific basis to advocate a diet moderate in total fat for the majority of individuals. Implicit to this position is that unsaturated fat has numerous beneficial health effects. However, because fat is energy dense, moderation in fat intake is essential for weight control. Consequently, a simple message to convey is to avoid diets that are very low and very high in fat. Moreover, within the range of a moderate-fat diet it is still important to individualize the total fat prescription. Nonetheless, the guiding principle is that moderation in total fat is the defining benchmark for a contemporary diet that reduces risk of chronic disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.095 | 0.266 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.010 |
| Bibliometrics | 0.030 | 0.018 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".